Nano Banana MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| GEMINI_API_KEY | Yes | Your Google AI API key from Google AI Studio (https://aistudio.google.com/apikey) |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| nanobanana_generate_imageA | Generate high-quality images from text descriptions using Google's Nano Banana models. This tool creates images from natural language prompts. For best results, be descriptive about:
Args:
Returns:
Examples:
Error Handling:
|
| nanobanana_edit_imageA | Edit an existing image using text prompts with Google's Nano Banana models. Provide an image and describe your desired changes. The model will:
The model maintains the original image's style and context while applying changes. Args:
Returns:
Examples:
Error Handling:
|
| nanobanana_compose_imagesA | Compose new images using multiple reference images with Nano Banana Pro. Use up to 14 reference images to:
Limits:
Args:
Returns:
Examples:
|
| nanobanana_list_modelsA | List available Nano Banana image generation models and their capabilities. Returns information about:
Args:
Returns:
|
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 4 tools
Each tool has a distinct and well-defined purpose: compose_images combines multiple reference images, edit_image modifies a single image, generate_image creates from text, and list_models provides metadata. The descriptions clearly differentiate their scopes, with no overlap or ambiguity in functionality.
All tool names follow a consistent snake_case pattern with the prefix 'nanobanana_' and a clear verb_noun structure (e.g., compose_images, edit_image, generate_image, list_models). This uniformity makes the set predictable and easy to navigate.
With 4 tools, this server is well-scoped for image generation and editing tasks. Each tool serves a unique and essential function in the workflow, from listing models to creating, editing, and composing images, without being overly sparse or bloated.
The tool set covers core image operations: generation, editing, composition, and model listing. Minor gaps might include batch processing or advanced filtering, but the surface supports typical agent workflows effectively, with no dead ends in the image manipulation lifecycle.